Search results for "FIBRILLATION"

An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms

2008

This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature- extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic s…

Complexity analysis of experimental cardiac arrhythmia

2014

International audience; To study the cardiac arrhythmia, an in vitro experimental model and Multielectrodes Array (MEA) are used. This platform serves as an intermediary of the electrical activities of cardiac cells and the signal processing / dynamics analysis. Through it the extracellular potential of cardiac cells is acquired, allowing a real-time monitoring / analyzing. Since MEA has 60 electrodes / channels dispatched in a rectangular region, it allows real-time monitoring and signal acquisition on multiple sites. The in vitro experimental model (cardiomyocytes cultures from new-born rats' heart) is directly prepared on the MEA. This carefully prepared culture has similar parameters as…

Quantification of synchronization during atrial fibrillation by Shannon entropy: Validation in patients and computer model of atrial arrhythmias

2005

Atrial fibrillation (AF), a cardiac arrhythmia classically described as completely desynchronized, is now known to show a certain amount of synchronized electrical activity. In the present work a new method for quantifying the level of synchronization of the electrical activity recorded in pairs of atrial sites during atrial fibrillation is presented. A synchronization index (Sy) was defined by quantifying the degree of complexity of the distribution of the time delays between sites by Shannon entropy estimation. The capability of Sy to discriminate different AF types in patients was assessed on a database of 60 pairs of endocardial recordings from a multipolar basket catheter. The analysis…

Registration and fusion of segmented left atrium CT images with CARTO electrical maps for the ablative treatment of atrial fibrillation

2005

This study aims to extract the interior surface of the left atrium (LA) and pulmonary veins (PVs) from threedimensional tomographic data and to integrate it with LA CARTO electrical maps. The separation of LA and PVs from other overlapping structures of the heart was performed processing 3D CT data by marker-controlled watershed segmentation and surface extraction. CARTO maps were then registered on the L A internal surface by a stochastic optimization algorithm based on simulated annealing. The residual registration error resulted inferior to 3 mm. The integration between electrophysiological and high resolved anatomic information of LA results feasible and may constitute a significant sup…

Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a Hybrid in silico and in vivo Dataset

2021

[EN] In patients with atrial fibrillation, intracardiac electrogram signal amplitude is known to decrease with increased structural tissue remodeling, referred to as fibrosis. In addition to the isolation of the pulmonary veins, fibrotic sites are considered a suitable target for catheter ablation. However, it remains an open challenge to find fibrotic areas and to differentiate their density and transmurality. This study aims to identify the volume fraction and transmurality of fibrosis in the atrial substrate. Simulated cardiac electrograms, combined with a generalized model of clinical noise, reproduce clinically measured signals. Our hybrid dataset approach combines in silico and clinic…

Cerebrovascular risk factors and clinical classification of strokes

2005

Cerebrovascular risk represents a progressive and evolving concept owing to the particular distribution of risk factors in patients with ischemic stroke and in light of the newest stroke subtype classifications that account for pathophysiological, instrumental, and clinical criteria. Age represents the strongest nonmodifiable risk factor associated with ischemic stroke, while hypertension constitutes the most important modifiable cerebrovascular risk factor, confirmed by a host of epidemiological data and by more recent intervention trials of primary (HOT, Syst-Eur, LIFE) and secondary (PROGRESS) prevention of stroke in hypertensive patients. To be sure, a curious relationship exists betwee…

2015

Background and purpose Silent atrial fibrillation (AF) and tachycardia (AT) are considered precursors of ischaemic stroke. Therefore, detection of paroxysmal atrial rhythm disorders is highly relevant, but is clinically challenging. We aimed to evaluate the diagnostic value of natriuretic peptide levels in the detection of paroxysmal AT/AF in a pilot study. Methods Natriuretic peptide levels were analysed in two independent patient cohorts (162 patients with arterial hypertension or other cardiovascular risk factors and 82 patients with retinal vessel disease). N-terminal-pro-brain natriuretic peptide (NT-proBNP) and BNP were measured before the start of a 7-day Holter monitoring period car…

Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps

2017

Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly diffe…

Ventricular Fibrillation and Tachycardia detection from surface ECG using time-frequency representation images as input dataset for machine learning

2017

Parameter-less ventricular fibrillation detection with time-frequency representation.Time-frequency representations are treated as images for a classifier.A comparison for four classifiers demonstrates the validity of the proposed method.The proposed technique could be applied to any signal and research field.This is a novel approach to signal analysis. Background and objectiveTo safely select the proper therapy for Ventricullar Fibrillation (VF) is essential to distinct it correctly from Ventricular Tachycardia (VT) and other rhythms. Provided that the required therapy would not be the same, an erroneous detection might lead to serious injuries to the patient or even cause Ventricular Fibr…

The supraventricular tachycardias: Proposal of a diagnostic algorithm for the narrow complex tachycardias

2013

AbstractThe narrow complex tachycardias (NCTs) are defined by the presence in a 12-lead electrocardiogram (ECG) of a QRS complex duration less than 120ms and a heart rate greater than 100 beats per minute; those are typically of supraventricular origin, although rarely narrow complex ventricular tachycardias have been reported in the literature.As some studies document, to diagnose correctly the NCTs is an arduous exercise because sometimes those have similar presentation on the ECG. In this paper, we have reviewed the physiopathological, clinical, and ECG findings of all known supraventricular tachycardias and, in order to reduce the possible diagnostic errors on the ECG, we have proposed …